Switching embedding model makes localrecall stop working with key error
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Description
I'm using LocalRecall from sources with the latest upstream 03f36d6 on Mac T8132 MacOS 15.5
It does work fine when using the default embedding model granite-embedding-107m-multilingual but as soon as I switch to another model it starts failing. I tried to use qwen3-embedding-8b and after re-running localrecall it stops working when uploading a file with the following error:
"ERROR","msg":"Failed to store file","!BADKEY":"failed to store file: couldn't add document '101': couldn't create embedding of document: error getting keys: error, status code: 500, status: 500 Internal Server Error, message: rpc error: code = InvalidArgument desc = Input content cannot be empty","source":{"filename":"/******/localrecall/routes.go","lineno":247}}
When searching the vector stores the same error gets thrown:
{"error":"Failed to search collection: couldn't create embedding of query: error getting keys: error, status code: 500, status: 500 Internal Server Error, message: rpc error: code = InvalidArgument desc = Input content cannot be empty"}
Afaik the qwen model should do the same as the granite one. I tried switching to it because the granite model produces very inaccurate results for me in German. I thought a larger model could probably do better finding the right embeddings to my queries. Regardless of that, I think localrecall should work with the qwen embedding model if it's available in localai so I opened this issue.
Switching back to granite model makes localrecall work fine.
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- Read the whole issue, then the project's contributing guide.
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Research direction
Start at routes.go:247 and reproduce the failure by configuring qwen3-embedding-8b, then compare file upload and search behavior with the granite-embedding-107m-multilingual model. Trace the embedding request until the LocalAI error reports empty input; done means uploads and searches work with the alternate model without the key error.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- go
- Domain
- ai, backend
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100